Appendices
D
Analysis of precipitation extremes and climate projections
Statistical Analysis
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Preface
1
Review of Linear Regression
2
Introduction to Time Series Analysis
3
Smoothing, Detrending, and Deseasonalizing
4
Autoregressive Moving Average (ARMA) Models
5
Autoregressive Integrated Moving Average (ARIMA) Models
6
Generalized Autoregressive Conditional Heteroskedasticity (GARCH) Models
7
Trend Detection
8
Time Series Regression with Trends
9
Time Series Regression with Correlated Errors
10
Causal Analysis Using Time Series
11
Panel Data Analysis
12
Model Evaluation and Forecasting
13
Spectral Analysis
References
Appendices
A
Weighted least squares
B
Generalized least squares
C
Synchrony of parametric trends
D
Analysis of precipitation extremes and climate projections
E
Practice exercises
Appendices
D
Analysis of precipitation extremes and climate projections
Appendix D — Analysis of precipitation extremes and climate projections
Text
C
Synchrony of parametric trends
E
Practice exercises